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A New Approximation to the Normal Distribution Quantile Function

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  • Paul M. Voutier

Abstract

We present a new approximation to the normal distribution quantile function. It has a similar form to the approximation of Beasley and Springer [3], providing a maximum absolute error of less than $2.5 \cdot 10^{-5}$. This is less accurate than [3], but still sufficient for many applications. However it is faster than [3]. This is its primary benefit, which can be crucial to many applications, including in financial markets.

Suggested Citation

  • Paul M. Voutier, 2010. "A New Approximation to the Normal Distribution Quantile Function," Papers 1002.0567, arXiv.org, revised Feb 2010.
    • Handle: RePEc:arx:papers:1002.0567
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    Cited by:

    1. Thomas Fung & Eugene Seneta, 2018. "Quantile Function Expansion Using Regularly Varying Functions," Methodology and Computing in Applied Probability, Springer, vol. 20(4), pages 1091-1103, December.

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